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Search Results (1,455)

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18 pages, 2798 KB  
Article
Exploring Low Energy Excitations in the d5 Iridate Double Perovskites La2BIrO6 (B = Zn, Mg)
by Abhisek Bandyopadhyay, Dheeraj Kumar Pandey, Carlo Meneghini, Anna Efimenko, Marco Moretti Sala and Sugata Ray
Condens. Matter 2025, 10(4), 53; https://doi.org/10.3390/condmat10040053 - 6 Oct 2025
Abstract
We experimentally investigate the structural, magnetic, transport, and electronic properties of two d5 iridate double perovskite materials La2BIrO6 (B = Mg, Zn). Notably, despite similar crystallographic structure, the two compounds show distinctly different magnetic behaviors. The M [...] Read more.
We experimentally investigate the structural, magnetic, transport, and electronic properties of two d5 iridate double perovskite materials La2BIrO6 (B = Mg, Zn). Notably, despite similar crystallographic structure, the two compounds show distinctly different magnetic behaviors. The M = Mg compound shows an antiferromagnetic-like linear field-dependent isothermal magnetization below its transition temperature, whereas the M = Zn counterpart displays a clear hysteresis loop followed by a noticeable coercive field, indicative of ferromagnetic components arising from a non-collinear Ir spin arrangement. The local structure studies authenticate perceptible M/Ir antisite disorder in both systems, which complicates the magnetic exchange interaction scenario by introducing Ir-O-Ir superexchange pathways in addition to the nominal Ir-O-B-O-Ir super-superexchange interactions expected for an ideally ordered structure. While spin–orbit coupling (SOC) plays a crucial role in establishing insulating behavior for both these compounds, the rotational and tilting distortions of the IrO6 (and MO6) octahedral units further lift the ideal cubic symmetry. Finally, by measuring the Ir-L3 edge resonant inelastic X-ray scattering (RIXS) spectra for both the compounds, giving evidence of spin–orbit-derived low-energy inter-J-state (intra t2g) transitions (below ~1 eV), the charge transfer (O 2p → Ir 5d), and the crystal field (Ir t2geg) excitations, we put forward a qualitative argument for the interplay among effective SOC, non-cubic crystal field, and intersite hopping in these two compounds. Full article
(This article belongs to the Section Quantum Materials)
26 pages, 3051 KB  
Article
Impact of Massive Electric Vehicle Penetration on Quito’s 138 kV Distribution System: Probabilistic Analysis for a Sustainable Energy Transition
by Paul Andrés Masache, Washington Rodrigo Freire, Leandro Gabriel Corrales, Ana Lucia Mañay and Pablo Andrés Reyes
World Electr. Veh. J. 2025, 16(10), 570; https://doi.org/10.3390/wevj16100570 - 5 Oct 2025
Viewed by 202
Abstract
The study evaluates the impact of massive electric vehicle (EV) penetration on Quito’s 138 kV distribution system in Ecuador, employing a probabilistic approach to support a sustainable energy transition. The rapid adoption of EVs, as projected by Ecuador’s National Electromobility Strategy, poses significant [...] Read more.
The study evaluates the impact of massive electric vehicle (EV) penetration on Quito’s 138 kV distribution system in Ecuador, employing a probabilistic approach to support a sustainable energy transition. The rapid adoption of EVs, as projected by Ecuador’s National Electromobility Strategy, poses significant challenges to the capacity and reliability of the city’s electrical infrastructure. The objective is to analyze the system’s response to increased EV load and assess its readiness for this scenario. A methodology integrating dynamic battery modeling, Monte Carlo simulations, and power flow analysis was employed, evaluating two penetration levels: 800 and 25,000 EVs, under homogeneous and non-homogeneous distribution scenarios. The results indicate that while the system can handle moderate penetration, high penetration levels lead to overloads in critical lines, such as L10–15 and L11–5, compromising normal system operation. It is concluded that specific infrastructure upgrades and the implementation of smart charging strategies are necessary to mitigate operational risks. This approach provides a robust framework for effective planning of EV integration into the system, contributing key insights for a transition toward sustainable mobility. Full article
(This article belongs to the Special Issue Impact of Electric Vehicles on Power Systems and Society)
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19 pages, 1327 KB  
Article
An IoT Architecture for Sustainable Urban Mobility: Towards Energy-Aware and Low-Emission Smart Cities
by Manuel J. C. S. Reis, Frederico Branco, Nishu Gupta and Carlos Serôdio
Future Internet 2025, 17(10), 457; https://doi.org/10.3390/fi17100457 - 4 Oct 2025
Viewed by 191
Abstract
The rapid growth of urban populations intensifies congestion, air pollution, and energy demand. Green mobility is central to sustainable smart cities, and the Internet of Things (IoT) offers a means to monitor, coordinate, and optimize transport systems in real time. This paper presents [...] Read more.
The rapid growth of urban populations intensifies congestion, air pollution, and energy demand. Green mobility is central to sustainable smart cities, and the Internet of Things (IoT) offers a means to monitor, coordinate, and optimize transport systems in real time. This paper presents an Internet of Things (IoT)-based architecture integrating heterogeneous sensing with edge–cloud orchestration and AI-driven control for green routing and coordinated Electric Vehicle (EV) charging. The framework supports adaptive traffic management, energy-aware charging, and multimodal integration through standards-aware interfaces and auditable Key Performance Indicators (KPIs). We hypothesize that, relative to a static shortest-path baseline, the integrated green routing and EV-charging coordination reduce (H1) mean travel time per trip by ≥7%, (H2) CO2 intensity (g/km) by ≥6%, and (H3) station peak load by ≥20% under moderate-to-high demand conditions. These hypotheses are tested in Simulation of Urban MObility (SUMO) with Handbook Emission Factors for Road Transport (HBEFA) emission classes, using 10 independent random seeds and reporting means with 95% confidence intervals and formal significance testing. The results confirm the hypotheses: average travel time decreases by approximately 9.8%, CO2 intensity by approximately 8%, and peak load by approximately 25% under demand multipliers ≥1.2 and EV shares ≥20%. Gains are attenuated under light demand, where congestion effects are weaker. We further discuss scalability, interoperability, privacy/security, and the simulation-to-deployment gap, and outline priorities for reproducible field pilots. In summary, a pragmatic edge–cloud IoT stack has the potential to lower congestion, reduce per-kilometer emissions, and smooth charging demand, provided it is supported by reliable data integration, resilient edge services, and standards-compliant interoperability, thereby contributing to sustainable urban mobility in line with the objectives of SDG 11 (Sustainable Cities and Communities). Full article
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29 pages, 6992 KB  
Article
Channel Optimization of Sandwich Double-Sided Cold Plates for Electric Vehicle Battery Cooling
by Hyoung-In Choi, Tae Seung Choi, Jeong-Keun Kook and Taek Keun Kim
Appl. Sci. 2025, 15(19), 10653; https://doi.org/10.3390/app151910653 - 1 Oct 2025
Viewed by 184
Abstract
Electric vehicle (EV) battery thermal management systems have gradually improved owing to the increasing power demand of EVs. This study aims to optimize the channel geometry of sandwich double-sided cold plates for EV battery cooling under 100% state of charge and 2C-rate charging [...] Read more.
Electric vehicle (EV) battery thermal management systems have gradually improved owing to the increasing power demand of EVs. This study aims to optimize the channel geometry of sandwich double-sided cold plates for EV battery cooling under 100% state of charge and 2C-rate charging conditions. For precise and accurate optimization, the conventional one-dimensional analysis model of the sandwich double-sided cold plate was converted into a three-dimensional computational fluid dynamics (CFD) model. Non-dimensional parameters were selected as the main variables of the channel geometry, and nine additional channel shapes were derived based on them. Battery modules with the derived channel shapes were subjected to CFD analysis in the Reynolds number range of 500 to 20,000. The goodness factor was calculated from these correlations, and optimization was performed using the Taguchi method. The results revealed that the wetted area of the channel had a greater impact on battery cooling than the number of channels. This study proposed more generalized design guidelines by employing non-dimensionalized parameters across a wide range of Reynolds numbers. The rectangular channel-based correlations developed in this study showed improved prediction accuracy compared to conventional annular pipe-based correlations and are expected to be applicable to various battery thermal management system designs in the future. Full article
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50 pages, 4498 KB  
Review
Reinforcement Learning for Electric Vehicle Charging Management: Theory and Applications
by Panagiotis Michailidis, Iakovos Michailidis and Elias Kosmatopoulos
Energies 2025, 18(19), 5225; https://doi.org/10.3390/en18195225 - 1 Oct 2025
Viewed by 380
Abstract
The growing complexity of electric vehicle charging station (EVCS) operations—driven by grid constraints, renewable integration, user variability, and dynamic pricing—has positioned reinforcement learning (RL) as a promising approach for intelligent, scalable, and adaptive control. After outlining the core theoretical foundations, including RL algorithms, [...] Read more.
The growing complexity of electric vehicle charging station (EVCS) operations—driven by grid constraints, renewable integration, user variability, and dynamic pricing—has positioned reinforcement learning (RL) as a promising approach for intelligent, scalable, and adaptive control. After outlining the core theoretical foundations, including RL algorithms, agent architectures, and EVCS classifications, this review presents a structured survey of influential research, highlighting how RL has been applied across various charging contexts and control scenarios. This paper categorizes RL methodologies from value-based to actor–critic and hybrid frameworks, and explores their integration with optimization techniques, forecasting models, and multi-agent coordination strategies. By examining key design aspects—including agent structures, training schemes, coordination mechanisms, reward formulation, data usage, and evaluation protocols—this review identifies broader trends across central control dimensions such as scalability, uncertainty management, interpretability, and adaptability. In addition, the review assesses common baselines, performance metrics, and validation settings used in the literature, linking algorithmic developments with real-world deployment needs. By bridging theoretical principles with practical insights, this work provides comprehensive directions for future RL applications in EVCS control, while identifying methodological gaps and opportunities for safer, more efficient, and sustainable operation. Full article
(This article belongs to the Special Issue Advanced Technologies for Electrified Transportation and Robotics)
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24 pages, 8578 KB  
Article
Electric Vehicle Charging Infrastructure with Hybrid Renewable Energy: A Feasibility Study in Jordan
by Ahmad Salah, Mohammad Shalby, Mohammad Al-Soeidat and Fadi Alhomaidat
World Electr. Veh. J. 2025, 16(10), 557; https://doi.org/10.3390/wevj16100557 - 30 Sep 2025
Viewed by 517
Abstract
Jordan Vision prioritizes the utilization of domestic resources, particularly renewable energy. The transportation sector, responsible for 49% of national energy consumption, remains central to this transition and accounts for around 28% of total greenhouse gas emissions. Electric vehicles (EVs) offer a promising solution [...] Read more.
Jordan Vision prioritizes the utilization of domestic resources, particularly renewable energy. The transportation sector, responsible for 49% of national energy consumption, remains central to this transition and accounts for around 28% of total greenhouse gas emissions. Electric vehicles (EVs) offer a promising solution to reduce waste and pollution, but they also pose challenges for grid stability and charging infrastructure development. This study addresses a critical gap in the planning of renewable-powered EV charging stations along Jordanian highways, where EV infrastructure is still limited and underdeveloped, by optimizing the design of a hybrid energy charging station using HOMER Grid (v1.9.2) Software. Region-specific constraints and multiple operational scenarios, including rooftop PV integration, are assessed to balance cost, performance, and reliability. This study also investigates suitable locations for charging stations along the Sahrawi Highway in Jordan. The proposed station, powered by a hybrid system of 53% wind and 29% solar energy, is projected to generate 1.466 million kWh annually at USD 0.0375/kWh, reducing CO2 emissions by approximately 446 tonnes annually. The findings highlight the potential of hybrid systems to increase renewable energy penetration, support national sustainability targets, and offer viable investment opportunities for policymakers and the private sector in Jordan. Full article
(This article belongs to the Section Charging Infrastructure and Grid Integration)
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43 pages, 2854 KB  
Review
Strategies for Enhancing BiVO4 Photoanodes for PEC Water Splitting: A State-of-the-Art Review
by Binh Duc Nguyen, In-Hee Choi and Jae-Yup Kim
Nanomaterials 2025, 15(19), 1494; https://doi.org/10.3390/nano15191494 - 30 Sep 2025
Viewed by 136
Abstract
Bismuth vanadate (BiVO4) has attracted significant attention as a photoanode material for photoelectrochemical (PEC) water splitting due to its suitable bandgap (~2.4 eV), strong visible light absorption, chemical stability, and cost-effectiveness. Despite these advantages, its practical application remains constrained by intrinsic [...] Read more.
Bismuth vanadate (BiVO4) has attracted significant attention as a photoanode material for photoelectrochemical (PEC) water splitting due to its suitable bandgap (~2.4 eV), strong visible light absorption, chemical stability, and cost-effectiveness. Despite these advantages, its practical application remains constrained by intrinsic limitations, including poor charge carrier mobility, short diffusion length, and sluggish oxygen evolution reaction (OER) kinetics. This review critically summarizes recent advancements aimed at enhancing BiVO4 PEC performance, encompassing synthesis strategies, defect engineering, heterojunction formation, cocatalyst integration, light-harvesting optimization, and stability improvements. Key fabrication methods—such as solution-based, vapor-phase, and electrochemical approaches—along with targeted modifications, including metal/nonmetal doping, surface passivation, and incorporation of electron transport layers, are discussed. Emphasis is placed on strategies to improve light absorption, charge separation efficiency (ηsep), and charge transfer efficiency (ηtrans) through bandgap engineering, optical structure design, and catalytic interface optimization. Approaches to enhance stability via protective overlayers and electrolyte tuning are also reviewed, alongside emerging applications of BiVO4 in tandem PEC systems and selective solar-driven production of value-added chemicals, such as H2O2. Finally, critical challenges, including the scale-up of electrode fabrication and the elucidation of fundamental reaction mechanisms, are highlighted, providing perspectives for bridging the gap between laboratory performance and practical implementation. Full article
21 pages, 5486 KB  
Article
Research on Mobile Energy Storage Configuration and Path Planning Strategy Under Dual Source-Load Uncertainty in Typhoon Disasters
by Bingchao Zhang, Chunyang Gong, Songli Fan, Jian Wang, Tianyuan Yu and Zhixin Wang
Energies 2025, 18(19), 5169; https://doi.org/10.3390/en18195169 - 28 Sep 2025
Viewed by 283
Abstract
In recent years, frequent typhoon-induced disasters have significantly increased the risk of power grid outages, posing severe challenges to the secure and stable operation of distribution grids with high penetration of distributed photovoltaic (PV) systems. Furthermore, during post-disaster recovery, the dual uncertainties of [...] Read more.
In recent years, frequent typhoon-induced disasters have significantly increased the risk of power grid outages, posing severe challenges to the secure and stable operation of distribution grids with high penetration of distributed photovoltaic (PV) systems. Furthermore, during post-disaster recovery, the dual uncertainties of distributed PV output and the charging/discharging behavior of flexible resources such as electric vehicles (EVs) complicate the configuration and scheduling of mobile energy storage systems (MESS). To address these challenges, this paper proposes a two-stage robust optimization framework for dynamic recovery of distribution grids: Firstly, a multi-stage decision framework is developed, incorporating MESS site selection, network reconfiguration, and resource scheduling. Secondly, a spatiotemporal coupling model is designed to integrate the dynamic dispatch behavior of MESS with the temporal and spatial evolution of disaster scenarios, enabling dynamic path planning. Finally, a nested column-and-constraint generation (NC&CG) algorithm is employed to address the uncertainties in PV output intervals and EV demand fluctuations. Simulations on the IEEE 33-node system demonstrate that the proposed method improves grid resilience and economic efficiency while reducing operational risks. Full article
(This article belongs to the Special Issue Control Technologies for Wind and Photovoltaic Power Generation)
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18 pages, 3750 KB  
Article
Optimal Guidance Mechanism for EV Charging Behavior and Its Impact Assessment on Distribution Network Hosting Capacity
by Xin Yang, Fan Zhou, Ran Xu, Yalin Zhong, Jingjing Yu and Hejun Yang
Processes 2025, 13(10), 3107; https://doi.org/10.3390/pr13103107 - 28 Sep 2025
Viewed by 201
Abstract
With the rapid growth in the penetration of Electric Vehicles (EVs), their large-scale uncoordinated charging behavior presents significant challenges to the hosting capacity of traditional distribution networks (DNs). The novelty of this paper lies in its methodology, which integrates a Markov Chain Monte [...] Read more.
With the rapid growth in the penetration of Electric Vehicles (EVs), their large-scale uncoordinated charging behavior presents significant challenges to the hosting capacity of traditional distribution networks (DNs). The novelty of this paper lies in its methodology, which integrates a Markov Chain Monte Carlo (MCMC) method for realistic load profiling with a bi-level optimization framework for Time-of-Use (TOU) pricing, whose effectiveness is then rigorously evaluated through an Optimal Power Flow (OPF)-based assessment of the grid’s hosting capacity. First, to compensate for the limitations of historical data, the MCMC method is employed to simulate the uncoordinated charging process of a large-scale EV fleet. Second, the bi-level optimization model is constructed to formulate a globally optimal TOU tariff that maximizes charging cost savings for EV users. At the same time, its lower-level simulates the optimal economic response of the EV user population. Finally, the change in the minimum daily hosting capacity is calculated based on the OPF. Case study simulations for IEEE 33-bus and IEEE 69-bus systems demonstrate that the proposed model effectively shifts charging loads to off-peak hours, achieving stable user cost savings of 20.95%. More importantly, the findings reveal substantial security benefits from this economic strategy, validated across diverse network topologies. In the 33-bus system, the minimum daily capacity enhancement ranged from 174.63% for the most vulnerable node to 2.44% for the strongest node. In the 69-bus system, vulnerable nodes still achieved a significant 78.62% improvement. This finding highlights the limitations of purely economic assessments and underscores the necessity of the proposed integrated framework for achieving precise, location-dependent security planning. Full article
(This article belongs to the Section Energy Systems)
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31 pages, 5070 KB  
Article
Crowd-Shipping: Optimized Mixed Fleet Routing for Cold Chain Distribution
by Fuqiang Lu, Yue Xi, Zhiyuan Gao, Hualing Bi and Shamim Mahreen
Symmetry 2025, 17(10), 1609; https://doi.org/10.3390/sym17101609 - 28 Sep 2025
Viewed by 396
Abstract
In fresh produce cold chain last-mile delivery, the highly dispersed customer base leads to exorbitant delivery costs, posing the greatest challenge for cold chain enterprises. Achieving a symmetrical balance between cost-efficiency, environmental sustainability, and service quality is a fundamental pursuit in logistics system [...] Read more.
In fresh produce cold chain last-mile delivery, the highly dispersed customer base leads to exorbitant delivery costs, posing the greatest challenge for cold chain enterprises. Achieving a symmetrical balance between cost-efficiency, environmental sustainability, and service quality is a fundamental pursuit in logistics system optimization. This paper proposes integrating the crowd-shipping logistics model—characterized by internet platform sharing and flexibility—into the delivery service. It incorporates and extends features such as cold chain delivery, mixed fleets using gasoline and diesel vehicles (GDVs), electric vehicles (EVs), partial charging strategies for EVs, and time-of-use electricity pricing into the crowd-shipping model. A joint delivery mode combining traditional professional delivery (using GDVs and EVs) with crowd-shipping is proposed, creating a symmetrical collaboration between centralized fleet management and distributed social resources. The challenges associated with utilizing occasional drivers (ODs) are analyzed, along with the corresponding compensation decisions and allocation-related constraints. A route optimization model is constructed with the objective of minimizing total cost. To solve this model, an Improved Whale Optimization Algorithm (IWOA) is proposed. To further enhance the algorithm’s performance, an adaptive variable neighborhood search is embedded within the proposed algorithm, and four local search operators are applied. Using a case study of 100 customer nodes, the joint delivery mode with OD participation reduces total delivery costs by an average of 24.94% compared to the traditional professional vehicle delivery mode, demonstrating a more symmetrical allocation of logistical resources. The experiments fully demonstrate the effectiveness of the joint delivery model and the proposed algorithm. Full article
(This article belongs to the Section Mathematics)
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15 pages, 9756 KB  
Article
Interaction of Oxygen Molecules with Fe Atom-Doped γ-Graphyne Surfaces: First-Principles Calculations
by Bin Zhao, Jiayi Yin, Zhuoting Xiong, Wentao Yang, Peng Guo, Meng Li, Haoxian Zeng and Jianjun Wang
Nanomaterials 2025, 15(19), 1479; https://doi.org/10.3390/nano15191479 - 27 Sep 2025
Viewed by 240
Abstract
The activation and dissociation of O2 molecules play a key role in the oxidation of toxic gas molecules and the oxygen reduction reaction (ORR) in hydrogen–oxygen fuel cells. The interactions between O2 molecules and the surfaces of Fe-doped γ-graphyne were systematically [...] Read more.
The activation and dissociation of O2 molecules play a key role in the oxidation of toxic gas molecules and the oxygen reduction reaction (ORR) in hydrogen–oxygen fuel cells. The interactions between O2 molecules and the surfaces of Fe-doped γ-graphyne were systematically explored, mainly adopting the combined method of the density functional theory with dispersion correction (DFT-D3) and the climbing image nudged elastic band (CI-NEB) method. The order of the formation energy values of these defective systems is Ef(FeC2) < Ef(FeC1) < Ef(FeD1) < Ef(VC1) < Ef(VD1) < Ef(VC2) < Ef(FeD2) < Ef(VD2), which indicates that the process of Fe dopant atoms substituting single-carbon atoms/double-carbon atoms is relatively easier than the formation of vacancy-like defects. The results of ab initio molecular dynamics (AIMD) simulations confirm that the doped systems can maintain structural stability at room temperature conditions. Fe-doped atoms transfer a certain amount of electrons to the adsorbed O2 molecules, thereby causing an increase in the O-O bond length of the adsorbed O2 molecules. The electrons obtained by the anti-bonding 2π* orbitals of the adsorbed O2 molecules are mainly derived from the 3d orbitals of Fe atoms. There is a competitive relationship between the substrate’s carbon atoms and the adsorbed O2 molecules for the charges transferred from Fe atoms. In the C1 and C2 systems, O2 molecules have a greater advantage in electron accepting ability compared to the substrate’s carbon atoms. The elongation of O-O bonds and the amount of charge transfer exhibit a positive relationship. More electrons are transferred from Fe-3d orbitals to adsorbed O2 molecules, occupying the 2π* orbitals of adsorbed O2 molecules, further elongating the O-O chemical bond until it breaks. The dissociation process of adsorbed O2 molecules on the surfaces of GY-Fe systems (C2 and D2 sites) involves very low energy barriers (0.016 eV for C2 and 0.12 eV for D2). Thus, our studies may provide useful insights for designing catalyst materials for oxidation reactions and the oxygen reduction reaction. Full article
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26 pages, 1356 KB  
Review
Equity Considerations in Public Electric Vehicle Charging: A Review
by Boyou Chen, Austin Moore, Bochen Jia, Kaihan Zhang and Mengqiu Cao
World Electr. Veh. J. 2025, 16(10), 553; https://doi.org/10.3390/wevj16100553 - 25 Sep 2025
Viewed by 373
Abstract
Public electric vehicle (EV) charging infrastructure is crucial for accelerating EV adoption and reducing transportation emissions; however, disparities in infrastructure access have raised significant equity concerns. This review synthesizes existing knowledge and identifies gaps regarding equity in EV public charging research. Following structured [...] Read more.
Public electric vehicle (EV) charging infrastructure is crucial for accelerating EV adoption and reducing transportation emissions; however, disparities in infrastructure access have raised significant equity concerns. This review synthesizes existing knowledge and identifies gaps regarding equity in EV public charging research. Following structured review protocols, 91 peer-reviewed studies from Scopus and Google Scholar were analyzed, focusing explicitly on equity considerations. The findings indicate that current research on EV public charging equity mainly adopts geographic information systems (GIS), network optimization, behavioral modeling, and hybrid analytical frameworks, yet lacks consistent normative frameworks for assessing equity outcomes. Equity assessments highlight four key dimensions: spatial accessibility, cost burdens, reliability and usability, and user awareness and trust. Socio-economic disparities, particularly income, housing tenure, and ethnicity, frequently exacerbate inequitable access, disproportionately disadvantaging low-income, renter, and minority populations. Additionally, infrastructure-specific choices, including charger reliability, strategic location, and pricing strategies, significantly influence adoption patterns and equity outcomes. However, the existing literature primarily reflects the contexts of North America, Europe, and China, revealing substantial geographical and methodological limitations. This review suggests the need for more robust normative evaluations of equity, comprehensive demographic data integration, and advanced methodological frameworks, thereby guiding targeted, inclusive, and context-sensitive infrastructure planning and policy interventions. Full article
(This article belongs to the Section Charging Infrastructure and Grid Integration)
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12 pages, 8239 KB  
Article
Impact of Molecular π-Bridge Modifications on Triphenylamine-Based Donor Materials for Organic Photovoltaic Solar Cells
by Duvalier Madrid-Úsuga, Omar J. Suárez and Alfonso Portacio
Condens. Matter 2025, 10(4), 52; https://doi.org/10.3390/condmat10040052 - 25 Sep 2025
Viewed by 271
Abstract
This study presents a computational investigation into the design of triphenylamine-based donor chromophores incorporating 2-(1,1-dicyanomethylene)rhodanine as the acceptor unit. Three molecular architectures (System-1 to System-3) were developed by introducing distinct thiophene-derived π-bridges to modulate their electronic and optical characteristics for potential application [...] Read more.
This study presents a computational investigation into the design of triphenylamine-based donor chromophores incorporating 2-(1,1-dicyanomethylene)rhodanine as the acceptor unit. Three molecular architectures (System-1 to System-3) were developed by introducing distinct thiophene-derived π-bridges to modulate their electronic and optical characteristics for potential application in bulk heterojunction organic solar cells (OSCs). Geometrical optimizations were performed at the B3LYP/6-31+G(d,p) level, while excited-state and absorption properties were evaluated using TD-DFT with the CAM-B3LYP functional. Frontier orbital analysis revealed efficient charge transfer from donor to acceptor moieties, with System-3 showing the narrowest HOMO–LUMO gap (1.96 eV) and the lowest excitation energy (2.968 eV). Charge transport properties, estimated from reorganization energies, indicated that System-2 exhibited the most favorable balance for ambipolar transport, featuring the lowest electron reorganization energy (0.317 eV) and competitive hole mobility. Photovoltaic parameters calculated with PC61BM as acceptor predicted superior Voc, Jsc, and fill factor values for System-2, resulting in the highest theoretical power conversion efficiency (10.95%). These findings suggest that π-bridge engineering in triphenylamine-based systems can significantly enhance optoelectronic performance, offering promising donor materials for next-generation OSC devices. Full article
(This article belongs to the Section Condensed Matter Theory)
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16 pages, 4259 KB  
Article
Morphology–Coordination Coupling of Fe–TCPP and g-C3N4 Nanotubes for Enhanced ROS Generation and Visible-Light Photocatalysis
by Nannan Zheng, Yulan Zhang, Chunlei Dong, Zhiming Chen and Jianbin Chen
Nanomaterials 2025, 15(19), 1465; https://doi.org/10.3390/nano15191465 - 24 Sep 2025
Viewed by 293
Abstract
Fe–porphyrin/g-C3N4 composites have emerged as promising visible-light photocatalysts, but their performance remains limited by inefficient charge separation and low reactive oxygen species (ROS) yield. Here, iron–tetra(4-carboxyphenyl) porphyrin (Fe–TCPP) was coupled with g-C3N4 nanotubes (CNNTs) via a facile [...] Read more.
Fe–porphyrin/g-C3N4 composites have emerged as promising visible-light photocatalysts, but their performance remains limited by inefficient charge separation and low reactive oxygen species (ROS) yield. Here, iron–tetra(4-carboxyphenyl) porphyrin (Fe–TCPP) was coupled with g-C3N4 nanotubes (CNNTs) via a facile self-assembly strategy, creating a morphology-coordinated system. Comprehensive characterization (XRD, FTIR, SEM/TEM, BET, UV–Vis diffuse reflectance, PL, XPS, and EPR) confirmed the structural integrity, electronic coupling, and ROS generation capability of the composites. Fe–TCPP incorporation narrowed the bandgap from 2.78 to 2.56 eV, prolonged the average carrier lifetime from 6.3 to 7.5 ns, and significantly enhanced the generation of •OH and 1O2. The optimized 1 wt% Fe–TCPP@CNNTs achieved complete Rhodamine B degradation within 30 min under visible light, with the highest two-stage apparent rate constants (k1 = 0.0964 min−1, k2 = 0.328 min−1). In addition, the hybrids retained over 90% activity after six consecutive runs, confirming their stability and recyclability. The synergistic effect of Fe–N coordination and nanotubular architecture thus promotes light harvesting, charge separation, and ROS utilization, offering a promising design principle for high-performance photocatalysts in environmental remediation. Full article
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30 pages, 9380 KB  
Article
Optimal Planning of EVCS Considering Renewable Energy Uncertainty via Improved Thermal Exchange Optimizer: A Practical Case Study in China
by Haocheng Liu, Yongli Ruan, Yunmei He, Shuting Yang and Bo Yang
Processes 2025, 13(10), 3041; https://doi.org/10.3390/pr13103041 - 23 Sep 2025
Viewed by 242
Abstract
With the rapid development of distributed energy and electric vehicles (EVs), the limited hosting capacity of distribution networks has severely impacted their economic dispatch and safe operation. To address these challenges, in this work, an optimal planning model considering the uncertainty of wind [...] Read more.
With the rapid development of distributed energy and electric vehicles (EVs), the limited hosting capacity of distribution networks has severely impacted their economic dispatch and safe operation. To address these challenges, in this work, an optimal planning model considering the uncertainty of wind and solar power output is proposed, aiming to determine the location and capacity of electric vehicle charging stations (EVCSs). The model seeks to minimize the total costs, voltage fluctuations, and network losses, subject to constraints such as EV user satisfaction and grid company satisfaction. A multi-objective heat exchange optimization algorithm under Gaussian mutation (MOTEO-GM) is employed to validate the model on an extended IEEE-33 bus system and a real-world case in the University Town area of Chenggong District, Kunming City. Simulation results indicate that, in the test system, voltage fluctuations and system power losses are decreased by 43.05% and 37.47%, respectively, significantly enhancing the economic operation of the distribution grid. Full article
(This article belongs to the Topic Advances in Power Science and Technology, 2nd Edition)
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